Integrating genomic resources to present full gene and putative promoter capture probe sets for bread wheat

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Abstract

Background

Whole-genome shotgun resequencing of wheat is expensive because of its large, repetitive genome. Moreover, sequence data can fail to map uniquely to the reference genome, making it difficult to unambiguously assign variation. Resequencing using target capture enables sequencing of large numbers of individuals at high coverage to reliably identify variants associated with important agronomic traits. Previous studies have implemented complementary DNA/exon or gene-based probe sets in which the promoter and intron sequence is largely missing alongside newly characterized genes from the recent improved reference sequences.

Results

We present and validate 2 gold standard capture probe sets for hexaploid bread wheat, a gene and a putative promoter capture, which are designed using recently developed genome sequence and annotation resources. The captures can be combined or used independently. We demonstrate that the capture probe sets effectively enrich the high-confidence genes and putative promoter regions that were identified in the genome alongside a large proportion of the low-confidence genes and associated promoters. Finally, we demonstrate successful sample multiplexing that allows generation of adequate sequence coverage for single-nucleotide polymorphism calling while significantly reducing cost per sample for gene and putative promoter capture.

Conclusions

We show that a capture design employing an “island strategy” can enable analysis of the large gene/putative promoter space of wheat with only 2 × 160 Mbp probe sets. Furthermore, these assays extend the regions of the wheat genome that are amenable to analyses beyond its exome, providing tools for detailed characterization of these regulatory regions in large populations.

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  1. Now published in GigaScience doi: 10.1093/gigascience/giz018

    Laura-jayne Gardiner 1Earlham Institute, Norwich, UKFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteThomas Brabbs 1Earlham Institute, Norwich, UKFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteAlina Akhunova 2Kansas State University, Department of Plant Pathology, Manhattan, KS, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteHikmet Budak 3Montana State University, Department of Plant Sciences and Plant Pathology, Bozeman, MT, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteTodd Richmond 4Roche Sequencing Solutions, Seattle, WA, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteSukwinder Singh 5CIMMYT, Obregon, MexicoFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteLeah Catchpole 1Earlham Institute, Norwich, UKFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteEduard Akhunov 2Kansas State University, Department of Plant Pathology, Manhattan, KS, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteAnthony Hall 1Earlham Institute, Norwich, UK6School of Biological Sciences, University of East Anglia, Norwich, UKFind this author on Google ScholarFind this author on PubMedSearch for this author on this site

    A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giz018 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

    These peer reviews were as follows:

    Reviewer 1: http://dx.doi.org/10.5524/REVIEW.101535 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.101536